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Robert Canales PhD

Robert  Canales PhD

Assistant Professor

Community, Environment & Policy Department

1295 N. Martin
Campus PO Box: 245210
Drachman Hall A229
Tucson, AZ 85724
(520) 621-0146


Robert Canales, PhD, earned his undergraduate degree in civil engineering from The University of Texas at Austin and graduate degrees in civil engineering, environmental engineering, and statistics from Stanford University.   He then transitioned to the field of environmental health as a fellow at the Harvard School of Public Health’s program in Exposure, Epidemiology & Risk.  Dr. Canales returned to Stanford University as an Acting Assistant Professor focusing on computational exposure simulation and chemical fate and transport models, and teaching courses in data analysis and exposure science.  Just prior to joining the University of Arizona, Dr. Canales was an Assistant Professor of Statistics at the New School, working with faculty and students across Parsons School of Design and Eugene Lang College.  Currently at the University of Arizona he collaborates with teams of researchers interested in machine learning and data mining, and the development of mechanistic models of health, risk, and environmental systems.  Robert mentors students from diverse backgrounds that are motivated to learn about interdisciplinary science, applied statistics, and computational methods in environmental science and health.

Research Synopsis

Dr. Canales' research interests span the fields of engineering, public health, statistics, and mathematics.  This multidisciplinary work takes many forms but primarily focuses on environmental and environmental health topics while using methodologies based in applied mathematics and systems science.  Primary themes include personal and residential multimedia exposures (including exposures to consumer products and microbial agents) and interventions, green/smart buildings and the built environment, contaminant transport, indoor air quality, infectious disease transmission, and risk analysis.  Methods include data mining/learning, analytics, agent-based modeling, dynamic compartmental modeling, Monte Carlo simulation, parameter estimation, uncertainty quantification, and nonparametric techniques. 


• Introduction to Health Science Statistics
• Introduction to Biostatistics
• Environmental and Occupational Health
• Applied Analysis of Environmental Data
• Modeling Exposures to Environmental Hazards

The University of Arizona